Failure probability estimation of steam turbine blades by enhanced Monte Carlo Method

• The Monte Carlo Method gives a very well approximation to failure analysis.
• Assessment of useful life has less randomness if considered the input data most influential.
• The damping is the variable most influential in evaluation of vibrations stresses.

Steam turbines are designed to work in stable operating conditions, including speed and load, to avoid mechanical stress variations. However, sometimes failures occur in the turbine components. The components having major breakdowns for fracture, an average of 75%, are the blades of the Low Pressure (LP) stage steam turbine. These blades produce around 10% of the output power turbines and 15% in some applications of combined cycle; generally longs, with a relatively low stiffness and such blades may present problems of high stress due to centrifugal forces. In this work probabilistic design procedure was applied to the group of ten blades of the LP stage steam turbine of 110 MW, in order to compute the stress changes and reliability due to variations in: damping, natural frequencies, vibration magnitude and density. The computed vibration stresses were analyzed by applying probability distributions and statistical parameters of input and output to compute the useful life. Monte Carlo technique and stochastic finite element method (SFEM) were applied. The results show that the Monte Carlo technique and SFEM are a good approach to estimate the useful life and reliability design of those blades.